Systems and methods for detecting markers on a roadway

ABSTRACT

System, methods, and other embodiments described herein relate to detecting markers on a roadway. In one embodiment, a method includes controlling a radar to transmit a scanning signal with defined characteristics. The radar is integrated with a vehicle that is traveling on the roadway. The method includes, in response to receiving a reflected signal resulting from the scanning signal interacting with the roadway, identifying the marker from the reflected signal according to an electromagnetic signature of the marker embodied in the reflected signal. The electromagnetic signature is a response induced within the defined characteristics of the scanning signal that is embodied within the reflected signal.

TECHNICAL FIELD

The subject matter described herein relates in general to systems andmethods for detecting markers on a roadway and, more particularly, tousing materials with highly contrasting electromagnetic properties toimprove the detectability of the markers.

BACKGROUND

Autonomous vehicles, also referred to as self-driving cars, navigateautonomously through an environment with minimal or no human input. Tonavigate autonomously, a vehicle determines a location within anenvironment so that various obstacles can be avoided and to ensure thatthe vehicle remains on the roadway. In general, autonomous vehicles mayuse various sensors including, for example, cameras to help the vehicledetect and identify obstacles in the environment. Thus, by way ofexample, the vehicle can use the cameras to obtain images of the roadwayand identify lane markers within the images. As a result, the vehiclecan, for example, determine whether it is presently within and keeping aparticular lane in relation to the lane markers.

However, identifying the lane markers in the described manner canpresent difficulties when, for example, precipitation (e.g., rain, snow,ice) is present on the roadway, when markers become worn, whenvisibility is poor (e.g., fog, snow), when a clear view is occluded bytraffic, and so on. Moreover, identifying the lane markers as describedprovides information about the lane markers themselves, but does notprovide additional information about the roadway or the surroundingenvironment.

SUMMARY

In one embodiment, example systems and methods relate to a manner ofdetecting markers according to a signature of the markers. For example,in order to improve the detectability of markers, in one embodiment, anelectromagnetic signature of the markers is altered. That is, a responseinduced within a reflected signal is controlled by, for example,altering properties of the markers to cause the particular response. Inone embodiment, the markers are installed within the roadway using, forexample, a material that absorbs electromagnetic radiation. Accordingly,when the vehicle scans the roadway, the marker contrasts withsurrounding segments because of the configured electromagnetic responseof the marker. In this way, the vehicle can identify the marker on theroadway even when the roadway is, for example, covered withprecipitation and/or the marker is not otherwise visible because ofpresent environmental conditions.

In one embodiment, a detection system for detecting a marker on aroadway is disclosed. The detection system includes one or moreprocessors and a memory that is communicably coupled to the one or moreprocessors. The memory stores a scanning module that includesinstructions that when executed by the one or more processors cause theone or more processors to control a radar to transmit a scanning signalwith defined characteristics. The radar is integrated with a vehiclethat is traveling on the roadway. The memory stores a detection moduleincluding instructions that when executed by the one or more processorscause the one or more processors to, in response to receiving areflected signal resulting from the scanning signal interacting with theroadway, identify the marker from the reflected signal according to anelectromagnetic signature of the marker embodied in the reflectedsignal. The electromagnetic signature is a response induced within thedefined characteristics of the scanning signal that is embodied withinthe reflected signal.

In one embodiment, a non-transitory computer-readable medium isdisclosed. The computer-readable medium stores instructions that whenexecuted by one or more processors cause the one or more processors toperform the disclosed functions. The instructions include instructionsto control a radar to transmit a scanning signal with definedcharacteristics, wherein the radar is integrated with a vehicle that istraveling on the roadway. The instructions include instructions to, inresponse to receiving a reflected signal resulting from the scanningsignal interacting with the roadway, identify the marker from thereflected signal according to an electromagnetic signature of the markerembodied in the reflected signal. The electromagnetic signature is aresponse induced within the defined characteristics of the scanningsignal that is embodied within the reflected signal.

In one embodiment, a method of detecting markers on a roadway isdisclosed. The method includes controlling a radar to transmit ascanning signal with defined characteristics. The radar is integratedwith a vehicle that is traveling on the roadway. The method includes, inresponse to receiving a reflected signal resulting from the scanningsignal interacting with the roadway, identifying the marker from thereflected signal according to an electromagnetic signature of the markerembodied in the reflected signal. The electromagnetic signature is aresponse induced within the defined characteristics of the scanningsignal that is embodied within the reflected signal.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of the specification, illustrate various systems, methods, andother embodiments of the disclosure. It will be appreciated that theillustrated element boundaries (e.g., boxes, groups of boxes, or othershapes) in the figures represent one embodiment of the boundaries. Insome embodiments, one element may be designed as multiple elements ormultiple elements may be designed as one element. In some embodiments,an element shown as an internal component of another element may beimplemented as an external component and vice versa. Furthermore,elements may not be drawn to scale.

FIG. 1 illustrates one embodiment of a vehicle within which systems andmethods disclosed herein may be implemented.

FIG. 2 illustrates one embodiment of a detection system that isassociated with detecting a marker on a roadway.

FIG. 3 illustrates one embodiment of a method that is associated withidentifying a marker on a roadway.

FIG. 4 illustrates one embodiment of a method associated with scanning aroadway for a marker.

FIG. 5 illustrates an overhead view of a roadway that includes markerswith an electromagnetic signature that contrasts with the surroundingsurface of the roadway.

FIG. 6 illustrates another overhead view of a roadway that includesmarkers with embedded codes.

FIG. 7 illustrates an overhead view of a roadway with markers havingdiffering electromagnetic characteristics from the surrounding surfaceof the roadway.

FIG. 8 illustrates one embodiment of a detection system that isassociated with identifying a roadway signature.

FIG. 9 illustrates a schematic of a vehicle equipped with an array ofradar sensors.

FIG. 10 illustrates one embodiment of a method that is associated withacquiring information from a roadway signature.

FIG. 11 illustrates a diagram of an embedded roadway signature.

FIG. 12 illustrates a graph representation of relative reflectivities ofthe embedded roadway signature of FIG. 12.

FIG. 13 illustrates an overhead view of a roadway with a roadwaysignature.

FIG. 14 illustrates one embodiment of a detection system that isassociated with localizing a vehicle according to a signature mapping.

FIG. 15 illustrates an overhead view of a roadway that includes acontinuous roadway signature randomly formed on a surface of theroadway.

FIG. 16 illustrates an overhead view of a roadway that includes acontinuous roadway signature formed from an aggregate embedded withinthe roadway.

FIG. 17 illustrates an overhead view of a roadway that includes aroadway signature marking boundaries of lanes.

FIG. 18 illustrates one embodiment of a method that is associated withlocalizing a vehicle on a roadway using a roadway signature.

DETAILED DESCRIPTION

As mentioned in the background, locating markers on a roadway and,similarly, determining a location of a vehicle on the roadway arecomplex tasks. Thus, as set forth herein, multiple embodiments aredisclosed relating to improving the detectability of markers on theroadway, embedding information within the roadway, and using theembedded information to facilitate localizing the vehicle on theroadway. Accordingly, as an initial matter, a general format of themarkers will be discussed along with how, either additionally oralternatively, information is embedded into the roadway. After thisbrief initial discussion, the description will turn to describingsystems, methods and other embodiments associated with detecting themarkers and acquiring embedded information from the roadway by avehicle.

As previously discussed, a vehicle can use lane markers painted onto asurface of the roadway in an attempt to visually identify lanes. Theselane markers are generally applied using paint or tape that is active inthe visible region of the electromagnetic spectrum. Thus, to detect themarkers, camera sensors of the vehicle provide images that are thenprocessed. However, many different circumstances can affect whether thelane markers are detected. These circumstances can include the presenceof precipitation (e.g., snow, ice, rain, etc.), environmental conditions(e.g., fog, smoke, etc.), lighting conditions (e.g., sun glare,headlights from oncoming traffic, etc.), and many other circumstances.Consequently, visually identifying the markers can suffer from variousdifficulties.

Therefore, in one embodiment, markers of the roadway are comprised of amaterial that causes the markers to contrast with a surrounding surfaceof the roadway in, for example, a range of wavelengths within theelectromagnetic spectrum that avoids the previously noted difficulties.Accordingly, the material can take on different forms depending on theparticular implementation. For example, the material can have ahyper-electromagnetic reflectivity that causes electromagnetic radiationto reflect back to an emission source with minimal attenuation. Inanother embodiment, the material absorbs electromagnetic radiation(e.g., radar absorbing material (RAM)) by attenuating theelectromagnetic radiation such that an area of the marker has acontrasting reflectivity which disperses and does not reflect radiationin comparison to the surrounding surface of the roadway. Thus, an areaof the marker can be of a comparatively low reflectivity in relation tothe surrounding roadway. Accordingly, by analogy a marker formed fromradar absorbing materials can be characterized as a black hole forelectromagnetic radiation of a particular wavelength or range ofwavelengths. Still, in a further embodiment, the marker can be comprisedof a combination of hyper-reflective material and radar absorbingmaterial forming a pattern that defines a binary relationship ofelectromagnetic reflectivities within the marker, which are bothdistinguished from the surrounding surface of the roadway.

In one embodiment, the materials that comprise the marker induce aresponse within a particular portion of the electromagnetic spectrumthat relates to radar signals. Thus, the materials can induce a responsein electromagnetic radiation having, for example, a wavelength of about2.7 mm to about 100 m. However, in one embodiment, the materials aregenerally focused on inducing a response in the centimeter to millimeterwavelength bands as may be implemented with a radar integrated into avehicle. While the response is generally discussed in relation to theelectromagnetic reflectivity of the material, in one embodiment, thematerial induces a shift in phase, wavelength, and/or polarity accordingto a defined amount between a scanning signal and a reflected signal. Ineither case, a wavelength of the scanning signal produced by the radaris generally unaffected by precipitation or other forms of atmosphericmoisture that can affect visible light. Thus, providing the markersformed from the noted materials along with configuring the vehicle toscan for the markers using the noted wavelengths can improve adetectability of the markers while avoiding the noted difficulties.

Moreover, in one embodiment, as noted, a pattern can be provided withinthe marker or separately in the roadway in either a structured (e.g., abar code) or an unstructured (e.g., randomized fingerprint) to embedinformation in the roadway. While roadway markers are generallydiscussed, various embodiments disclosed herein encompass using thenoted materials to embed information within the roadway outside of theconfines of the markers themselves. That is, for example, the materialscan be applied within a lane between lane markers, interspersed betweenlane markers and/or other traffic markers, and so on. As an additionalmatter, in general, the material has a neutral coloring in the visiblespectrum and thus blends with the markers or the roadway when separatefrom the markers. Furthermore, when combined with the markers, thematerial may be colored in a similar fashion as the marker to blend withthe marker. Accordingly, the material can be applied to the roadway inmany different configurations to facilitate marking and localization onthe roadway.

To review the marker composition in a broad context, the generalapproach is to form the markers and/or the patterns within the roadwayfrom a material (e.g., paint, tape, aggregate, etc.) that significantlycontrasts with surrounding surfaces in relation to electromagneticreflectivity within non-visible portions of the electromagneticspectrum. In this way, the vehicle can detect and use the variousmarkings for identifying lanes and acquiring information about theroadway when the roadway is covered with precipitation and/or whenconditions are otherwise averse to visually detecting the markers. Thus,using the noted materials to supplement the markers and/or to embedadditional information in the roadway is a robust approach thatovercomes the noted difficulties.

Additional aspects of the markers and the roadway signature will bediscussed along with the provided embodiments of the vehicle. Referringto FIG. 1, an example of a vehicle 100 is illustrated. As used herein, a“vehicle” is any form of motorized transport. In one or moreimplementations, the vehicle 100 is an automobile. While arrangementswill be described herein with respect to automobiles, it will beunderstood that embodiments are not limited to automobiles. In someimplementations, the vehicle 100 may be any other form of poweredtransport that, for example, includes a radar sensor and thus benefitsfrom detecting the materials in the roadway as discussed herein.

The vehicle 100 also includes various elements. It will be understoodthat in various embodiments it may not be necessary for the vehicle 100to have all of the elements shown in FIG. 1. The vehicle 100 can havedifferent combinations of the various elements shown in FIG. 1. Further,the vehicle 100 can have additional elements to those shown in FIG. 1.In some arrangements, the vehicle 100 may be implemented without one ormore of the elements shown in FIG. 1. While the various elements areshown as being located within the vehicle 100 in FIG. 1, it will beunderstood that one or more of these elements can be located external tothe vehicle 100. Additionally, the elements shown may be physicallyseparated by large distances.

Some of the possible elements of the vehicle 100 are shown in FIG. 1 andwill be described along with subsequent figures. However, a descriptionof many of the elements in FIG. 1 will be provided after the discussionof FIGS. 2-18 for purposes of brevity of this description. Additionally,it will be appreciated that for simplicity and clarity of illustration,where appropriate, reference numerals have been repeated among thedifferent figures to indicate corresponding or analogous elements. Inaddition, the discussion outlines numerous specific details to provide athorough understanding of the embodiments described herein. Those ofskill in the art, however, will understand that the embodimentsdescribed herein may be practiced using various combinations of theseelements.

In either case, the vehicle 100 includes a detection system 170 that isimplemented to perform methods and other functions as disclosed hereinrelating to, for example, detecting markers on a roadway and/or todetecting patterns of electromagnetic responsive material embeddedwithin the roadway. The noted functions and methods will become moreapparent with a further discussion of the figures.

With reference to FIG. 2, one embodiment of the detection system 170 ofFIG. 1 is further illustrated. The detection system 170 is shown asincluding a processor 110 from the vehicle 100 of FIG. 1. Accordingly,the processor 110 may be a part of the detection system 170, thedetection system 170 may include a separate processor from the processor110 of the vehicle 100, or the detection system 170 may access theprocessor 110 through a data bus or another communication path. In oneembodiment, the detection system 170 includes a memory 210 that stores ascanning module 220 and a detection module 230. The memory 210 is arandom-access memory (RAM), read-only memory (ROM), a hard-disk drive, aflash memory, or other suitable memory for storing the modules 220 and230. The modules 220 and 230 are, for example, computer-readableinstructions that when executed by the processor 110 cause the processor110 to perform the various functions disclosed herein.

Accordingly, the scanning module 220 generally includes instructionsthat function to control the processor 110 to retrieve data from sensorsof a sensor system 120. In other words, the scanning module 220 includesinstructions to acquire data from a radar sensor 123, a LIDAR sensor124, a camera 126, and so on. In one embodiment, the scanning module 220functions to control the radar sensor 123 to scan a currentlocation/environment using a scanning signal which interacts withsurfaces in the environment to produce a reflected signal that the radarsensor 123 receives. In general, the radar sensor 123 is configured toemit the scanning signal with defined characteristics. For example, theradar sensor 123 generates the scanning signal with a definedwavelength, frequency, intensity, and polarity.

Consequently, the scanning module 220 can use the reflected signal todetermine characteristics of the surface (e.g., the roadway) accordingto a wavelength, frequency, intensity, and polarity of the reflectedsignal that specifically relate to the scanning signal. While fourseparate characteristics of the scanning signal and the reflected signalare generally described, it should be appreciated that fewercharacteristics (e.g., intensity alone) may be analyzed to determineaspects of the roadway. In either case, the characteristics of thereflected signal embody properties of the roadway in how thoseproperties differ from the original scanning signal.

By way of example, when the scanning module 220 controls the radarsensor 123 to scan the roadway for a marker that is comprised of radarabsorbing material, the detection module 230 analyzes properties of aresulting reflected signal for changes in the intensity in comparison tothe scanning signal and also in comparison to reflected signals fromsurrounding segments of the roadway. In this way, the detection module230 can distinguish the marker from the surrounding roadway even whenthe roadway is covered in precipitation.

Furthermore, the radar sensor 123 itself can be implemented in severaldifferent forms. In one embodiment, the radar sensor 123 is aforward-facing radar located in a front grill, front bumper, or otherforward-facing portion of the vehicle 100. Additionally, in oneembodiment, the radar sensor 123 is provided for purposes such asdetecting other vehicles/obstacles, for active cruise control (ACC),and/or for collision avoidance systems. Thus, in one embodiment, thedetection system 170 sniffs or otherwise passively obtains informationfrom the radar sensor 123. In other embodiments, the radar sensor 123 isa dedicated device of the detection system 170.

Additionally, the radar sensor 123 is, in one embodiment, an array ofradar sensors. Thus, the array of radar sensors may include side-facingsensors, forward-facing sensors, rear-facing sensors, and so on.Alternatively, or additionally, in one embodiment, the radar sensor 123includes a set of radar sensors (e.g., one, two, three, or more) thatare directed to a surface of the roadway and are attached to anunderside of the vehicle 100. Further aspects of the radar sensor 123will be discussed along with particular embodiments subsequently.However, it should be appreciated that a particular form and arrangementof the radar sensor 123 may vary depending on aspects of the specifiedembodiment.

In either case, the scanning module 220, in one embodiment, continuouslyreceives reflected signals from the roadway as the vehicle 100progresses along a path. Thus, the scanning module 220 is, in oneembodiment, continuously, or, at least semi-continuously scanning theroadway. In alternative embodiments, the scanning module 220 selectivelyscans the roadway at regular intervals (e.g., every 0.1 seconds). Ineither case, the scanning module 220 scans the roadway and providesreflected signals as a result of the scanning.

In one embodiment, the detection module 230 generally includesinstructions that function to control the processor 110 to analyze thereflected signals for an electromagnetic signature that correlates witha marker on the roadway. As previously noted, the electromagneticsignature is the distinct response produced in the reflected signal bythe marker on the roadway. Thus, the detection module 230, in oneembodiment, continuously monitors for indicators of the electromagneticsignature within the received reflected signals (e.g., phase shift,intensity shift, etc.). It should be noted, that in an instance wherethe marker is characterized by attenuating the scanning signal and thusnot producing the reflected signal because the scanning signal isotherwise dispersed or dissipated, the detection module 230 monitors foran absence of the reflected signal over an area of the marker and apresence of the reflected signal in adjacent areas.

Accordingly, in one embodiment, the detection module 230 generates amatrix of surface reflectivities according to a coordinate systemrelative to the roadway. Consequently, the detection module 230 canscore grid locations within the matrix according to intensity levels ofreflected signals. Subsequently, the detection module 230 comparesadjacent cells of the matrix in order to identify contrasting cells anddetect the markers. Moreover, the detection module 230 can also identifyembedded codes (e.g., barcodes) in this manner by identifying a patternwithin the matrix that corresponds to an embedded code.

Accordingly, in one embodiment, the detection system 170 includes thedatabase 240. The database 240 is, in one embodiment, an electronic datastructure stored in the memory 210 or another data store and that isconfigured with routines that can be executed by the processor 110 foranalyzing stored data, providing stored data, organizing stored data,and so on. Thus, in one embodiment, the database 240 stores data used bythe modules 220 and 230 in executing various functions. In oneembodiment, the database 240 includes a marker schema 250. The markerschema 250 stores, for example, information for decoding embeddedbarcodes, identifying various types of markers (e.g., lane markers,traffic markers, etc.) according to shapes and locations within theroadway, and so on.

Additional aspects of identifying markers will be discussed in relationto FIG. 3. FIG. 3 illustrates a flowchart of a method 300 that isassociated with using a radar to detect markers on a roadway. Method 300will be discussed from the perspective of the detection system 170 ofFIGS. 1 and 2. While method 300 is discussed in combination with thedetection system 170, it should be appreciated that the method 300 isnot limited to being implemented within the detection system 170, but isinstead one example of a system that may implement the method 300.

At 310, the scanning module 220 controls a radar to transmit a scanningsignal with defined characteristics. In one embodiment, the scanningmodule 220 actively controls the radar sensor 123 to transmit thescanning signal. As previously mentioned, the scanning signal isgenerated according to the defined characteristics in order to, forexample, provide the detection module 230 with the ability to measurechanges to the scanning signal as embodied by the reflected signal.

Moreover, while a single scanning signal is discussed, in oneembodiment, the scanning module 220 can control the radar sensor 123 togenerate scanning signals with different defined characteristics and/ormultiple sub-sensors of a sensor array that comprises the radar sensor123 to simultaneously generate scanning signals. The scanning module 220may use scanning signals with different defined characteristicsaccording to, for example, different environmental conditions. That is,the scanning module 220 can select different intensities, wavelengthsand so on to optimize the scanning for different conditions, such aswhen precipitation is present. Because atmospheric moisture canattenuate certain wavelengths of electromagnetic radiation, the scanningmodule 220 may select a wavelength of the scanning signal when rain,snow, or ice are detected that does not experience interference orexperiences minimal interference from the moisture. In this way, thedetection system 170 can detect the marker when visible detectionapproaches would be otherwise ineffective.

Additionally, the scanning module 220, in one embodiment, scans an areaof the roadway where the marker is expected to be located.Alternatively, in another embodiment, the scanning module 220continuously scans across a width of the roadway that is covered by theradar sensor 123. In either case, the scanning module 220 can scan ahorizontal dimension (e.g., width) of the roadway in addition to alongitudinal dimension as the vehicle 100 progresses along a path on theroadway. In this way, the scanning module 220 can detect the marker whenthe vehicle 100 is off-center within the lane and also when markers arepresent within the lane itself as opposed to being at an edge of thelane.

At 320, the scanning module 220 receives a reflected signal resultingfrom the scanning signal interacting with the roadway. As previouslynoted, the marker is configured with one or more materials that induce aresponse in the scanning signal to produce the reflected signal withproperties that are indicative of the presence of the marker. Thus, thereflected signal represents a modified form of the scanning signal andembodies properties of whatever surface reflected the scanning signal.Accordingly, the marker modifies characteristics of the scanning signalto produce the reflected signal. Thus, as previously mentioned, thereflected signal may be transformed in comparison to the scanning signalthrough a shift in phase (i.e., a temporal shift), a shift in intensity(e.g., a reduction from radar absorbing material), and so on. In eithercase, the scanning module 220 acquires the detected characteristics ofthe reflected signal and communicates the reflected signal to thedetection module 230 over a data bus or other communication pathway forfurther processing.

At 330, the detection module 230 identifies the marker from thereflected signal. In one embodiment, the detection module 230 monitorsreflected signals for an electromagnetic signature that is indicative ofthe marker as the reflected signals are received. As previously noted,the markers may be configured using different materials and may beencoded with various patterns to convey more detailed information. Thus,the detection module 230 can monitor for multiple differentelectromagnetic signatures as defined by the marker schema 250. As anexample, the reflectivity of sequential markers may be alternatedbetween hyper-reflective and highly dispersing in a particularpattern/order (e.g., morse code) to convey information in a binaryformat. Moreover, in one embodiment, the markers may be configured withvarious degrees of reflectivity to implement a ternary system forconveying information or a system of a higher granularity depending on aresolution of the radar sensor 123. Whichever particular system isimplemented, the detection module 230 identifies the markers accordingto the distinct electromagnetic signature.

Additional details about how the detection module 230 identifies themarker will be discussed in relation to FIG. 4. FIG. 4 illustrates aflowchart of a method 400 that is associated with analyzing reflectedsignals to identify markers in a roadway. Method 400 will be discussedfrom the perspective of the detection system 170 of FIGS. 1 and 2. Whilemethod 400 is discussed in combination with the detection system 170, itshould be appreciated that the method 400 is not limited to beingimplemented within the detection system 170, but is instead one exampleof a system that may implement the method 400. Moreover, as previouslyindicated, method 400 is a further detailed illustration of block 330from FIG. 3. Thus, for purposes of the subsequent discussion aspectsrelating to scanning the roadway and receiving the reflected signal arereferenced in relation to blocks 310 and 320 of method 300. As anadditional note, in various embodiments, the method 400 may beimplemented with a portion of the blocks described along with FIG. 4.However, a comprehensive discussion of different aspects of the method400 is provided to illustrate options for identifying the marker in awide scope.

At 410, the detection module 230 searches for indicators of the markerin the reflected signal. In one embodiment, the detection module 230searches for the electromagnetic signature of the marker by, forexample, comparing characteristics (e.g., detected intensity) against adetection threshold. The detection threshold defines a value for thespecified characteristic(s) for which the marker is likely present.Thus, the detection module 230 parses or otherwise analyzes incomingdata about reflected signals from the roadway to identify particularintensity values, polarities, wavelengths, and/or other characteristics.In general, the marker schema 250 can be defined as a policy or templatefor various types of markers and which values satisfy the detectionthreshold to trigger a detection or further processing.

For example, the marker schema 250, in one embodiment, definescorrelations between different markers and characteristics of thedifferent markers. Thus, for each different type of marker, the markerschema 250 can specify a detection threshold, an electromagneticsignature, a shape of the marker, an area on the roadway where the makeris likely located, and/or other information about the maker.

Thus, for a marker that is characterized by a low reflectivity from thepresence of radar absorbing material within the marker, the markerschema 250 can define a contrasting region in the roadway that ischaracterized by a highly contrasting reflectivity in comparison tosurrounding sections of the roadway as an indicator. Thus, the detectionmodule 230 searches for the marker by detecting relatively low-intensityvalues in the reflected signal proximate to average or expectedintensity values. By contrast, for a marker that is characterized by aphase shift, the schema 250 can specify a phase region in the roadwaythat is characterized by a defined phase shift relative to the definedcharacteristics of the scanning signal. Thus, in the example of thephase region, the detection module 230 searches for a particular phasevalue within the reflected signal.

Moreover, while electromagnetic signatures of the markers have beendiscussed, in one embodiment, the embedded signatures are geometricpatterns that are embodied as physical ridges of, for example, variablethickness and spacing which produce unique characteristics within thereflected signals. Accordingly, the marker schema 250 can specify a widerange of types for the markers along with metadata used by the detectionmodule 230 for detecting the markers.

At 420, the detection module 230 determines whether the electromagneticsignature is present in the reflected signal. In one embodiment, thedetection module 230 undertakes a deeper analysis of the reflectedsignal at 420 as triggered by an initial superficial detection at 410.That is, the detection module 230, for example, determines whethervalues (e.g., intensity values) of the reflected signal match theelectronic signature specified by the marker schema 250.

If the values do not correlate, then the detection module 230 proceedsto continue searching as discussed in relation to block 410. However, ifthe detection module 230 determines that there is a match, then thedetection module 230 proceeds by determining further aspects of themarker at 430 and 440.

At 430, the detection module 230 determines a location of the markerwithin the roadway. In one embodiment, the detection module 230 locatesthe marker in relation to relative segments of the roadway to, forexample, identify a type of the marker. That is, the detection module230 can further infer information about the marker by determining if themarker is located at an edge of the roadway, within a lane of theroadway, between lanes, and so on. For example, when the marker ischaracterized by a contrasting region of reflectivity in the roadway,the detection module 230 analyzes the reflected signal to determinewhether the contrasting region aligns with expected marker locations foran inside lane marker (e.g., lane divider or centerline), an outsidelane marker (e.g., roadway edge marker), a traffic marker within a lane(e.g., lane restriction identifiers), and so on. In this way, thedetection module 230 can determine aspects of the lane markers beyondsimply identifying a presence of the markers.

At 440, the detection module 230 determines a shape of the marker. Inone embodiment, the detection module 230 determines the shape in orderto confirm the type of the marker. For example, the detection module 230can outline the region associated with the marker as identified from thereflected signal(s). Thus, when the marker is characterized by thecontrasting region, the detection module 230 outlines the contrastingregion to determine the shape or at least a general shape of the marker.Because the marker may include imperfections from wear, damage, thepresence of foreign objects, or other circumstances, the detectionmodule 230 can compare the generated outline with shapes of known typesof markers as defined by the marker schema 250. This comparison cancorrelate the marker with a particular type of marker according to, forexample, a confidence interval depending on how closely the outlineconforms to the defined shape. In this way, the detection module 230 canfurther correlate the marker with a particular defined type.Additionally, in further embodiments, where the marker includes anembedded barcode or other embedded information, the detection module 230outlines the contrasting regions to identify and retrieve the barcodefrom the marker.

At 450, the detection module 230 determines whether the marker satisfiesa threshold for identifying the marker. In one embodiment, the detectionmodule 230 determines whether the determined shape, the location, and/orthe detected electromagnetic signature satisfy a marker threshold thatindicates a confidence interval for accepting the marker as beingvalidly identified. In other words, the detection module 230 verifieswhether the detected aspects of the marker correlate with a known typeof marker in order to filter out errant anomalies in the roadway. Thus,if the detected aspects do not sufficiently satisfy the marker threshold(e.g., >85% correlation), then the detection module 230 proceeds withsearching for markers as discussed at block 410. However, if the shape,location, and electromagnetic signature do correlate with a known typeof marker and thus satisfy the marker threshold, then the detectionmodule 230 outputs a positive identification of the marker at 460. Whilethe shape, location, and electromagnetic signature are discussed asfactors used by the detection module 230 for determining the presence ofthe marker, in various embodiments, one or more of the described factorsmay be omitted and/or other factors may be used by the detection module230 when assessing the marker.

Additionally, in one embodiment, at 460, the detection module 230outputs a location and identifier of the marker to, for example, anautonomous driving module 160 or other component of the vehicle 100 inorder to provide a notification about the marker. The autonomous drivingmodule 160 can use the identified marker to, for example, facilitatecontrolling the vehicle 100 and maintaining a current lane.

In further embodiments, at 460, the detection module 230 decodes theembedded information from the marker and provides the embeddedinformation. For example, as part of determining the shape, at 440, thedetection module 230 can identify an embedded barcode, QR code, binarycode, ternary code, or other form of encoding within the marker orbetween multiple markers. Further aspects of identifying the encodingwill be discussed subsequently. However, it should be appreciated thatthe marker can be configured with different encodings by selectivelylocating the materials with the particular electromagnetic signatureswithin the marker. That is, areas that produce the reflected signal withthe particular electromagnetic signatures can be selectively applied tothe marker to embed codes within the marker.

Thus, the detection module 230 can extract the codes from the marker(s)as part of, for example, determining the electromagnetic signature at420 and the shape at 440. A resulting output of the detection module 230is the roadway code, which can then be decoded using, for example,techniques for reading barcodes. Thus, the detection module 230 uses theoutput or an identifier (e.g., alpha-numeric value) of the output tolookup information about the roadway or information associated with apresent location. In one embodiment, the detection module 230 referencesthe marker schema 250 using the decoded identifier from the marker toobtain information about upcoming roadway features, a current geospatiallocation, or other information that may be desirable to convey throughthe marker.

As further explanation of the markers, FIG. 5 illustrates a roadway 500that is illustrated with lane markers 510, 520, and 530. The marker 510is a centerline lane dividing marker. The markers 520 and 530 are edgemarkers for the roadway 500. As illustrated in FIG. 5, the vehicle 100is traveling along a path within a right lane and the detection system170 is controlling the radar sensor 123 to scan the roadway 500 formarkers. Thus, all three of the markers 510, 520, and 530 can beprovided with electromagnetic signatures and/or geometric signatures;however, the centerline 510 will be the present focus.

Accordingly, a magnified view of two of the centerline markers 510 isshown with markers 540 and 550 to better illustrate a generalcomposition of the markers 510. As illustrated, the markers 510 arecomprised of radar absorbing material (RAM) or another material thatgenerally disperses radar signals without returning the signals to asource. Thus, the overall view of the roadway 500 can be considered avisible light view where the markers 510, 520, and 530 may appear ascommon lane markers. However, the magnified view of the markers 540 and550 is illustrated in a non-visible portion of the electromagneticspectrum to highlight contrasting regions of the markers in comparisonto a surface of the roadway 500. That is, the markers 540 and 550generally disperse electromagnetic radiation in a 25 GHz frequency band.Thus, as shown in FIG. 5 internal regions of the markers 540 and 550 donot reflect radar signals of the indicated frequency or reflect signalswith a reduced intensity. Consequently, the markers 540 and 550 appearto be dark in color in comparison to surrounding segments of the roadway500. This high contrast configuration within the specified radar bandmeans that the vehicle 100 can scan the roadway 500 and detect themarkers 510 by identifying the contrasting regions. While notspecifically illustrated, the markers 520 and 530 may also provide asimilar response as the markers 510 in relation to the scanning radarsensor 123 of the vehicle 100.

FIG. 6 illustrates a similar configuration as FIG. 5. For example, FIG.6 illustrates markers 610, 620, and 630 on a roadway 600 with a similarconfiguration to FIG. 5. However, upon further inspection ofelectromagnetic responses provided when scanning the markers 640 and650, embedded barcodes become evident. That is, the centerline markers640 and 650 of FIG. 6 include embedded barcodes. Thus, as the detectionsystem 170 scans the roadway 600 using the radar sensor 123, thereflected signals received from the markers 640 and 650 can be used toreconstruct the shape of the barcodes embedded using the radar absorbingmaterials in the markers 640 and 650. The detection module 230 can thendecode the barcodes to obtain information about the roadway 600 orupcoming features (e.g., traffic patterns, traffic signs, etc.) of theroadway 600. It should be noted that, while the centerline markers 640and 650 are illustrated as including the barcodes, in other embodiments,the barcodes may take different forms (e.g., QR codes, APRIL tags, etc.)and/or may be embodied within different markers such as the edge markers620 and 630, embedded within a center area of the lane without anassociated visible marker, embedded in fewer or more of the centerlinemarkers 610, and so on. In general, the electromagnetic signature andcodes formed from selectively placing the electromagnetic signatures canbe embedded within the roadway 600 at any desired location.

FIG. 7 illustrates a further embodiment of how the markers on a roadway700 can be implemented and detected by the vehicle 100. For example, asillustrated, the roadway 700 includes a similar configuration of visiblemarkers as FIGS. 5 and 6. That is, the roadway 700 includes centerlinemarkers 710, and edge markers 720 and 730. The vehicle 100 is travelingalong a path and is scanning the roadway 700 using a scanning signal(s)780. As illustrated in FIG. 7, markers 740, 750, 760, and 770 areprovided in a magnified view and according to a response provided bythose markers when reflecting the signals 780. The signals 780 aregenerally radar signals that are provided in a radar frequency band(e.g., 25 GHz) of the electromagnetic spectrum.

Accordingly, the illustrated responses of the markers 740, 750, 760, and770 illustrate different electromagnetic signatures that may beimplemented separately or in various combinations between the markers710. Moreover, different signatures may be implemented in the markersdepending on a type of the marker. That is, for example, the markers 730may be implemented using a first electromagnetic signature, the markers720 may be implemented according to a second electromagnetic signature,the markers 710 may be implemented according to a third electromagneticsignature, and so on. Thus, the different types of markers may correlatewith separate electromagnetic signatures according to the type. As anadditional note, the electromagnetic signatures in the markers may beimplemented in a continuous manner where the marker is a solid line or,in alternative embodiments, may be varied according to, for example,changing aspects of the roadway.

In either case, different electromagnetic signatures can be encoded indifferent dashes of the markers 710 or in segments of the markers of themarkers 720 and 730, as a manner of, for example, encoding informationusing a binary code, a ternary code, or another resolution of code. Inone embodiment, the separate forms of electromagnetic signatures areused to embed a Morse code between dashes, an opcode such as that usedby a computer processor, and so on. As illustrated in FIG. 7, the marker740 has a low-reflectivity signature, marker 750 has a phase shiftsignature, the marker 760 has a high-reflectivity signature, and themarker 770 has a different phase shift signature than the marker 750.Accordingly, as illustrated, the markers have four separate options forelectromagnetic signatures. However, it should be appreciated thatseparate granularities of reflectivity can also be implemented and canbe implemented in combination with further aspects such as phase shiftsto provide a range of possible electromagnetic signatures for themarkers. In this way, different markers can be encoded using differentelectromagnetic signatures and/or different signatures can beimplemented between or within markers to embed codes. Consequently, thedetection system 170 can acquire information (e.g., roadway information,navigation information, location information, etc.) from the encodedmarkers as the vehicle 100 travels along the roadway.

Roadway Signature

With reference to FIG. 8, an alternative embodiment of the detectionsystem 170 of FIGS. 1 and 2 is illustrated. As illustrated in FIG. 8,the detection system 170 includes elements similar to those discussed inrelation to FIG. 2; however, a general configuration of the elements maydiffer. For example, the database 240, in FIG. 8, is illustrated asstoring a signature lookup 800 and a signature schema 810. It should benoted that while the database 240 is not illustrated as including themarker schema 250 in FIG. 8, in various embodiments, the database 240may still include the marker schema 250 in addition to the signaturelookup 800 and the signature schema 810. Moreover, in FIG. 8, thedetection system 170 is illustrated as including an identificationmodule 820 and a signature module 830. In various embodiments, themodules 820 and 830 can include elements similar to the modules 220 and230 in addition to further aspects as discussed in relation to FIG. 8.

Moreover, in FIG. 8, the detection system 170 is shown as including theprocessor 110 from the vehicle 100 of FIG. 1. Accordingly, as previouslynoted, the processor 110 may be a part of the detection system 170, thedetection system 170 may include a separate processor from the processor110 of the vehicle 100, or the detection system 170 may access theprocessor 110 through a data bus or another communication path. In oneembodiment, the detection system 170 includes the memory 210 that storesthe identification module 820 and the signature module 830. The modules820 and 830 are, for example, computer-readable instructions that whenexecuted by the processor 110 cause the processor 110 to perform thevarious functions disclosed herein. Accordingly, the identificationmodule 820 generally includes instructions that function to control theprocessor 110 to retrieve data from sensors of the sensor system 120 ina similar manner as discussed in relation to the scanning module 220 ofFIG. 2. That is, the identification module 820, in one embodiment,controls the radar sensor 123 to transmit a scanning signal and toreceive a reflected signal resulting from the scanning signal reflectingfrom surfaces in a surrounding environment.

As a brief explanation of one example configuration of the radar sensor123, consider FIG. 9. FIG. 9 illustrates a view of a roadway 900 withthe vehicle 100 traveling within a lane. The lane is defined in theroadway 900 by a centerline marker 905 and an edge marker 910. The radarsensor 123 is illustrated as being attached to an undercarriage of thevehicle 100 in an area between or forward of front wheels of the vehicle100. In the illustrated embodiment, the radar sensor 123 is comprised ofan array of three separate sensors that each individually transmit andreceive electromagnetic radiation with a wavelength within a radar bandof the electromagnetic spectrum. For example, the wavelength may be acentimeter-wavelength, a millimeter-wavelength or another wavelength ofradiation that is suitable for scanning the roadway 900. Additionally,while three sensors are illustrated, in various implementations, thearray can be comprised of more sensor or fewer sensors. For example, inone embodiment, more sensors (e.g., 5 sensors) may be provided toincrease a resolution of information obtained from a surface of theroadway. In either case, the radar sensor 123 is, in one embodiment,controlled by the identification module 820 to scan for signatureswithin the roadway such as roadway signature 915.

Further description of the roadway signature 915 and other roadwaysignatures will now be provided before proceeding with the discussion ofFIG. 8. Accordingly, a roadway signature is, in one embodiment, apattern in the roadway that is comprised of sections of one or morematerials that produce a response within electromagnetic radiation thatencounters the provided materials. Accordingly, a reflected signal fromthe roadway signature embodies aspects of the roadway signature inelectromagnetic characteristics of the reflected radiation. In oneembodiment, the material that forms the roadway signature is a materialthat has particular reflective properties, phase shift properties,and/or other properties that induce a response in electromagneticradiation as discussed in relation to the markers in FIGS. 2-7. In oneembodiment, the material is applied to the roadway in a pattern that isunstructured or randomized to form the roadway signature. That is, theroadway signature is, for example, applied in a splatter paintingmanner, a drip painting manner (also referred to as JacksonPollock-style), or another randomized form of application. Accordingly,in one embodiment, the pattern that comprises the roadway signatureincludes sections of contrasting reflectivity that are randomlydispersed on a surface of the roadway within a driving lane.

Accordingly as illustrated in FIG. 9, the roadway signature includes acombination of curved lines, blobs, and other random forms. It should beappreciated that the roadway signature 915 is illustrated in this mannerbut may, additionally or alternatively, be comprised of randomizedshapes (e.g., rocks coated with the described material) and/or otherforms. Moreover, the roadway signature is illustrated as being visibleon the roadway 900; however, the illustrated form of the signature 915is for purposes of illustration, and an actual roadway signature asapplied to a roadway may not be responsive in the visible lightspectrum. In still a further embodiment, the roadway signature is ageometric pattern characterized by carved ridges or other shapes on asurface of the roadway. Thus, the scanning signal can interact with thegeometric pattern to produce the reflected signal according tocharacteristics that embody the roadway signature.

Accordingly, returning to FIG. 8, the signature module 830 generallyincludes instructions that function to control the processor 110 tocompute an identifier of a roadway signature when detected by theidentification module 820. In one embodiment, the signature module 830computes the identifier from the characteristics of the roadwaysignature as embodied by the reflected signal and correlated from amapping of the characteristics over the roadway. As one example, thesignature module 830 can analyze the roadway signature to identifyminutiae in the roadway signature that can then be correlated togenerate the identifier according to, for example, a fingerprintingheuristic. Thus, similar to how a fingerprint can be decomposed intoidentifying aspects and used to generate a biometric identifier, theroadway signature is processed to produce the noted identifier thatuniquely identifies the roadway signature.

Additional details about how the detection system 170 acquiresinformation from roadway signatures will be discussed in relation toFIG. 10. FIG. 10 illustrates a flowchart of a method 1000 that isassociated with analyzing reflected signals to identify markers in aroadway. Method 1000 will be discussed from the perspective of thedetection system 170 of FIGS. 1 and 8. While method 1000 is discussed incombination with the detection system 170, it should be appreciated thatthe method 1000 is not limited to being implemented within the detectionsystem 170, but is instead one example of a system that may implementthe method 1000.

At 1010, the identification module 820 controls the radar sensor 123 totransmit a scanning signal. As discussed previously, in relation toblock 310 of method 300, the scanning signal is a radar signal that isgenerated to have defined characteristics. For example, the scanningsignal has a defined wavelength, intensity, and frequency. Moreover,while a single scanning signal is discussed, it should be appreciatedthat the scanning signal can be comprised of multiple separate scanningsignals from separate sensors within a radar array and/or separatesignals over time with the respective signals having the same definedcharacteristics or, for example, different characteristics forrespective ones of the separate signals.

At 1020, the identification module 820 receives a reflected signalresulting from the scanning signal interacting with the roadway. In oneembodiment, the identification module 820 continuously or at leastsemi-continuously receives reflected signals from the roadway at as aresult of transmitting the scanning signal. The reflected signals areindicative of properties of the surface of the roadway. For example,depending on properties of materials that comprise the roadway, thedefined characteristics are altered in different ways to produce thereflected signals. Thus, the reflected signals embody aspects of thesurface of the roadway. Consequently, when the roadway signature isapplied to the roadway using a material that attenuates the scanningsignal, the reflected signal will have a characteristic lower intensityor not be reflected at all. Similarly, if the applied materials hasproperties that induce a phase shift, then the reflected signal willhave a phase, in comparison with the scanning signal, that is shifted bythe defined amount.

At 1030, the identification module 820 analyzes the reflected signal todetermine whether a roadway signature is present. In one embodiment, theidentification module 820 monitors reflected signals received at 1020for indicators of the roadway signature. For example, the indicators caninclude responses induced within the reflected signals. The response isrepresented by the modified characteristics of the reflected signal suchas the change in intensity, shift in phase, and so on. Thus, upondetecting the particular indicia of the roadway signature over adiscrete portion of the roadway, the identification module 820 can, forexample, provide a notification to the signature module 830 to computethe identifier at 1040. Otherwise, the identification module 820continues to monitor for a roadway signature. Before proceeding itshould be noted, that the roadway signature, in one embodiment, is adiscrete pattern that is embedded within the roadway. Accordingly, theidentification module 820, may continuously buffer the reflected signaland, upon identifying indicators of the roadway signature in thereflected signal, the identification module 820, transforms thereflected signal into a mapping or otherwise saves the reflected signalto memory so that the signature module 830 can further analyze thereflected signal.

As one example, consider FIG. 11, which illustrates an overhead view ofa roadway segment with a roadway signature 1100. The roadway signature1100 is illustrated as a false color image since the roadway signatureis generally not responsive to visible light. In either case, theroadway signature 1100 is a discrete randomized pattern in the roadwaythat, for example, spans a width (i.e., horizontal x-dimension) or partof the width of the roadway. Additionally, the roadway signature has adiscrete length (longitudinal y-dimension) along the roadway. Thus, asthe vehicle 100 progresses over the roadway and the detection system 170is scanning, reflected signals from t1 are initially acquired with t2,t3 and t4 following subsequently. Thus, the identification module 820identifies the reflected signals from aspects obtained over the portioncorresponding with t1 that indicate the presence of the roadwaysignature 1100. Accordingly, the identification module 820, in oneembodiment, saves the reflected signals from t1, t2, t3, and t4 to thememory 210 or another memory/buffer. While the identification module 820is mentioned as storing the reflected signals, in one embodiment, theidentification module 820 stores detected characteristics of thereflected signals such as intensity/amplitude, wavelength, polarity,phase, etc.

Moreover, in one embodiment, the identification module 820 mapscharacteristics from the acquired reflected signals into a mapping thatcorrelates with coordinates of a surface of the roadway. For example,with reference to FIG. 12, one example of a mapping 1200 as may beproduced by the identification module 820 is illustrated. The mapping1200 is a grid including columns and rows with individual cellscorresponding to different sections of the roadway. Each of the rowscorresponds with an additional area along the roadway in, for example, alongitudinal y-dimension whereas each column corresponds to a differenthorizontal component in the x-dimension. Thus, in one embodiment, as thevehicle 100 progresses along the roadway, the identification module 820populates cells of the mapping 1200 according to characteristics of thereflected signals that correlate with each cell.

For example, as illustrated in FIG. 12, the identification module 820progressively populates each row of the mapping 1200 that correspondswith sections along the roadway as the vehicle 100 travels.Additionally, as illustrated, the mapping 1200 is generally directed toa binary detection of whether the roadway signature is detected for acell or not. However, it should be appreciated that, in variousembodiments, the identification module 820 can represent aspects of theroadway signature with additional resolution by indicating a specificvalue for a characteristic and/or indicating multiple characteristicsfor each of the cells. However, for purposes of simplicity ofillustration, a single characteristic indicating signal intensity hasbeen illustrated. More specifically, the mapping 1200 indicates whethera particular area of the roadway is minimally reflective and includes,for example, radar absorbing material that correlates with the presenceof the roadway signature 1100 of FIG. 11.

The identification module 820 indicates whether an intensity of thereflected signal or an overall lack of a reflected signal is indicativeof the roadway signature and indicates an affirmative identification bymarking a corresponding cell. Thus, as illustrated, the mapping 1200corresponds to the minimally reflective areas of the roadway signature1100. Because various anomalies may exist within or on the roadway atvarious times, the identification module 820, in one embodiment, markscells according to when characteristics of the reflected signal satisfya threshold value. Thus, as one example, when the identification module820 receives a reflected signal from portion 1105 of the roadwaysignature, the identification module 820 compares an intensity valueagainst the threshold value and marks the cell 1205 upon confirming thelow intensity.

By contrast, when the identification module 820 receives a reflectedsignal from portion 1110 of the signature 1100, the mapping at cell 1210is not marked because the intensity value associated with the traceportion 1110 is not sufficient. Consequently, anomalies, random noise,and other errors can be filtered from the mapping 1200. Accordingly, theidentification module 820, in one embodiment, provides the mapping 1200as an output to the signature module 830 for further processing.

At 1040, the signature module 830 computes an identifier from thereflected signal as a function of features uniquely associated with theroadway signature that are embodied within the reflected signal. In oneembodiment, the signature module 830 processes the reflected signal(s)according to a fingerprinting heuristic to generate the identifier as aunique characterization of the roadway signature. It should be noted,that in various embodiments, an image or mapping of the roadwaysignature can be generated from the reflected signals and then comparedby the signature module 830 against other known roadway signaturesstored in, for example, the database 240 to identify the particularsignature. However, storing a library of signatures may be acomputationally intensive effort. Thus, in one embodiment, the detectionsystem 170 computes the identifier as a placeholder or uniquecharacterization of the roadway signature in order to, for example,avoid storing a whole form of the roadway signature.

Thus, in one embodiment, the signature module 830 computes theidentifier over a multi-step process that begins by marking or otherwiseidentifying features in the roadway signature. By way of example, thesignature module 830 parses the mapping of the roadway signature toidentify features within the roadway signature that can be used toidentify the signature. For example, the signature module 830 can searchthe mapping for shapes or other registering minutiae that can be used tocharacterize the roadway signature. In one embodiment, the signatureschema 810 defines the features, which are then used for comparison bythe signature module 830.

With reference to the mapping 1200 of FIG. 12, the signature schema 810can define shapes according to grids that correlate with the roadwaysignature. For example, the signature schema 810 can define aconfiguration of cells such as cells 1215 and 1220 which generallyresemble an upside down “v” as being a feature. As another example, thesignature schema 810 can define a column of cells such as cells 1225and/or diagonal cells 1230 as being features. Consequently, as thesignature module 830 parses the mapping 1200, the features 1215, 1220,1225, and 1230 can be marked. In general, as part of marking thefeatures, the signature module 830 can list the features according tometadata (e.g., feature ID and coordinates) or otherwise modify themapping 1200 to indicate the presence of the noted features.

Thereafter, the signature module 830 determines relationships betweenthe features by, for example, calculating relative positions between thefeatures (e.g., direction and distance) and/or determining othercorrelating aspects. In either case, the signature module 830 quantizesthese identifying minutiae and the relationships between the identifyingminutiae. In one embodiment, the features and the relationships are usedby the signature module 830 to produce a graph or other data structurethat embodies the elements.

In either case, the signature module 830 computes the identifier byapplying a heuristic to the quantized features. In one embodiment, theheuristic is a fingerprinting heuristic or other algorithm as may beused to generate biometric identifiers. Moreover, the algorithm can be acryptographic algorithm that outputs an authentication code, key, orother numeric value as the identifier upon accepting the quantizedfeatures. In either case, the resulting identifier uniquelycharacterizes the roadway signature so that the roadway signature can beidentified when encountered by the vehicle 100. Additionally, as afurther matter, producing the identifier according to a cryptographicalgorithm and the signature schema 810 can facilitate avoiding spoofingof the roadway signature by malicious interests since the identifier isnot easily reproduced without the exact roadway signature, knowledge ofthe signature schema 810 and the employed algorithm.

As an alternative and/or additional embodiment, the signature module 830can produce the identifier by translating the mapping into a binarysequence or other quantized format and computing a checksum over thesequence. With either approach, the identifier that is provided as anoutput by the signature module 830 can be used for different purposesrelative to the location of the roadway signature as discussed at 1050.

At 1050, the signature module 830 provides information according to theidentifier. In one embodiment, the signature module 830 retrievesinformation about the roadway or features of the roadway that areproximate to the roadway signature associated with the identifier. Forexample, consider FIG. 13, which illustrates an overhead view of aroadway 1300. The roadway 1300 is illustrated as including the vehicle100, the roadway signature 1100 of FIG. 11, a stop sign 1310, and anassociated stop marker 1320. Accordingly, as the vehicle 100 travelsover the roadway signature 1100 toward the stop sign 1310, the detectionsystem 170 identifies the roadway signature and computes the associatedidentifier. Subsequently, the signature module 830 uses the identifierto, for example, execute a lookup against the signature lookup 800.Consequently, the signature module 830 acquires information about theroadway 1300 from the signature lookup 800. In the present example, theinformation identifies the stop sign 1310 and the distance to the marker1320. In other embodiments, the information may include GPS coordinatesof the navigation information, roadway information (e.g., load weightlimits, grade percentages, traffic patterns, etc.), and so on.

Moreover, while the lookup operation is generally discussed as being alocal operation, in one embodiment, the database 240 and the signaturelookup 800 are located remotely from the detection system 170 and thesignature module 830 provides the identifier in a communication over acellular or other communication network to query a service forinformation relating to the roadway 1300. Thus, information that isprovided in response from the service can be dynamically updatedaccording to weather conditions, traffic, constructions, and so on inaddition to other information about the roadway 1300 itself.

As an additional note, the roadway signatures as discussed in relationto FIGS. 8 and 10 are generally understood to be discrete. That is, theroadway signatures in relation to the embodiment of method 1000 are notpervasive throughout the roadway, but are instead of a defined lengthalong the roadway and breadth across the roadway. Thus, as the detectionand acquisition of information relates to the embodiments disclosed inrelation to the method 1000, the roadway signatures can be strategicallyplaced to facilitate controlling an autonomous vehicle by embeddingidentifiers associated with information relevant to navigating theparticular section of roadway.

Roadway Signature with Localization

With reference to FIG. 14, an alternative embodiment of the detectionsystem 170 of FIGS. 2 and 8 is illustrated. As illustrated in FIG. 14,the detection system 170 includes elements similar to those discussed inrelation to FIGS. 2 and 8, however, a general configuration of theelements may differ. For example, the database 240, in FIG. 14, isillustrated as storing the signature schema 810 from FIG. 8 in additionto a signature mapping 1400. It should be noted that while the database240 is not illustrated as including the marker schema 250 or thesignature lookup 800, in various embodiments, the database 240 may stillinclude the noted elements in addition to the signature mapping 1400.Additionally, the database 240, as previously noted, may be acloud-based or distributed memory that is accessed over a communicationslink. Moreover, in FIG. 14, the detection system 170 is illustrated asincluding a monitoring module 1410 and a localization module 1420. Invarious embodiments, the modules 1410 and 1420 can include elementssimilar to the modules 220, 230, 820 and 830 in addition to furtheraspects as discussed in relation to FIG. 14.

Furthermore, in FIG. 14, the detection system 170 is shown as includingthe processor 110 from the vehicle 100 of FIG. 1. Accordingly, aspreviously noted, the processor 110 may be a part of the detectionsystem 170, the detection system 170 may include a separate processorfrom the processor 110 of the vehicle 100, or the detection system 170may access the processor 110 through a data bus or another communicationpath. In one embodiment, the detection system 170 includes the memory210 that stores the monitoring module 1410 and the localization module1420. The modules 1410 and 1420 are, for example, computer-readableinstructions that when executed by the processor 110 cause the processor110 to perform the various functions disclosed herein. Accordingly, themonitoring module 1410 generally includes instructions that function tocontrol the processor 110 to retrieve data from sensors of the sensorsystem 120 in a similar manner as discussed in relation to the scanningmodule 220 of FIG. 2 and the identification module 820 of FIG. 8. Thatis, the monitoring module 1410, in one embodiment, controls the radarsensor 123 to transmit a scanning signal and to receive a reflectedsignal resulting from the scanning signal reflecting from surfaces in asurrounding environment. In particular, the monitoring module 1410, inone embodiment, controls a radar array as illustrated in FIG. 9 to scana surface of a roadway on which the vehicle 100 is traveling.

Moreover, the monitoring module 1410 is, in one embodiment, configuredin a similar manner as the identification module 820 of FIG. 8. Thus,the monitoring module 1410 controls the radar sensor 123 to transmit ascanning signal and to receive a resulting reflected signal from theroadway. Furthermore, the monitoring module 1410, in one embodiment, isalso configured to detect the roadway signature and compute anidentifier in a similar manner as discussed in relation to the signaturemodule 830 of FIG. 8.

However, because the roadway signature is, in one embodiment, continuousor at least semi-continuous along the roadway, the monitoring module1410 also includes instructions to acquire a fix on the roadwaysignature, as will be discussed in further detail subsequently. Asfurther explanation of the general format of the continuous roadwaysignature, FIGS. 15-17 will be discussed prior to further discussion ofthe detection system 170. Accordingly, with reference to FIG. 15, oneexample of a roadway 1500 is illustrated that includes two lanes 1505and 1510. Each of the lanes 1505 and 1510 include a separate continuousroadway signature 1515 and 1520. The continuous roadway signatures 1515and 1520 are similar to the roadway signature 1100 of FIG. 11 with theexception of being substantially continuous along the roadway instead ofdiscrete. Thus, the roadway signatures 1515 and 1520 are comprised ofthe same or similar configurations of materials (e.g., radar absorbingmaterial) and generally blend in with the roadway surface 1500 as viewedin the visible light spectrum.

The magnified view 1525 of a segment of the roadway signature 1515illustrates a general form of the roadway signature 1515, which issimilar to the roadway signature 1520. That is, the roadway signature1515 is comprised of a material applied to the roadway within the lane1510. The material is applied in a randomized manner that can becharacterized as a drip or splash painting method. Accordingly, aspictured in the view 1525 the segment of the roadway signature 1515includes lines and curves of varying thickness, various spots and shapesof differing sizes and orientations, overlapping/intersecting lines, andother features that may be expected when using the described applicationmethod. Furthermore, as illustrated in FIG. 15, the roadway signatures1520 and 1515 are applied to be substantially centered within therespective lanes 1505 and 1510. Thus, as will be discussed in greaterdetail subsequently, the detection system 170 can use a placement of theroadway signature 1515 to guide the vehicle 100 along the roadway 1500when, for example, operating in an autonomous mode.

As a further example of how the continuous roadway signature may beimplemented, consider FIG. 16, which illustrates a roadway 1600. Theroadway is illustrated in a similar configuration as the roadway 1500,however, instead of the roadway signature being constrained to a centerarea of each lane, the roadway signature of FIG. 16 is pervasivethroughout the roadway 1600. That is, the roadway signature illustratedin FIG. 16 is distributed across the whole roadway 1600 without beingapplied to just a center region of each lane as with the roadwaysignatures 1515 and 1520 of FIG. 15. A manner of embedding the roadwaysignature as shown in FIG. 16 can include mixing stone or otheraggregate with particular electromagnetic properties into asphalt,concrete or whichever material is used to construct the roadway 1600.Moreover, the stone or other aggregate may be coated with a paint, epoxyor other coating that imparts the aggregate with the particularelectromagnetic properties. As one example, stone may be coated with aradar absorbing material (RAM) and mixed with other materials that areused to construct the roadway 1600 at a prescribed ratio. In furtherembodiments, different aggregate that has been modified to have separateelectromagnetic properties may be mixed together to form the roadwaysignature as shown in FIG. 16. Thus, stones with a relatively highreflectivity, a relatively low reflectivity, with phase shiftingproperties, and so on can be mixed together and embedded within theroadway 1600 to form the roadway signature.

A magnified view 1610 of the roadway, illustrates a response to ascanning radar signal of the aggregate that forms the roadway signature.As shown in the view 1610, the aggregate is mixed into the roadway 1600at a, for example, 10% rate by way of area in comparison to the asphalt.However, in other embodiments, the mixing rate can be higher, lower, orvaried along a length of the roadway 1600 to provide greater variabilityto the roadway signature.

A further example of the continuous roadway signature is illustrated inrelation to FIG. 17. FIG. 17 includes continuous roadway signatures1710, 1720, and 1730. As with the previous illustrations of the roadwaysignatures, the signatures 1710, 1720, and 1730 are shown in afalse-color format since the signatures otherwise blend in with theroadway under visible light. In either case, the signatures 1710 and1730 are edge marker roadway signatures that are continuous alongrespective edges of the roadway 1700. The roadway signature 1720 is anexample of a centerline roadway signature that is continuous along acenterline of the roadway 1700. Accordingly, the roadway signatures1710, 1720, and 1730 generally correspond to lane markers of the roadway1700 instead of being located within a center region of each lane aswith the roadway signatures 1515 and 1520. Thus, the roadway signatures1710, 1720, and 1730 supplement the visible markers as a form of markinglanes of the roadway 1700 for detection using radar signals. Moreover,as with the roadway signatures discussed along with FIG. 10, the roadwaysignatures 1710, 1720, and 1730 can be processed to produce anidentifier or series of identifiers that correlate various informationassociated with the particular segments of the roadway.

Furthermore, because the signatures 1710, 1720, and 1730 are locatedalong portions of the roadway that experience less wear, the signatures1710, 1720, and 1730 may also avoid degradation from being located asshown. As a further aspect of the continuous roadway signatures,detection of the signatures using radar signals avoids difficulties withvisually perceiving the signatures since the electromagnetic radiationcan penetrate snow, ice and other precipitation along with certaindebris that may otherwise occlude a visible light camera from imaginglane markers.

While the various roadway signatures of FIGS. 15, 16, 17, and 11 areillustrated and discussed separately, in various embodiments, thesignatures can be combined into a single roadway together and/or atvarious different locations to separately provide information.Similarly, in one embodiment, the lane markers can be modified toinclude the electromagnetic signature as discussed in relation to FIGS.3 and 4 along with providing the discrete and/or continuous roadwaysignatures of FIGS. 11, 15, 16, and 17. In either case, further detailsabout the continuous roadway signatures will be discussed in relation toFIG. 18.

Additional details about how the detection system 170 acquires a fix onthe continuous roadway signatures and localizes the vehicle will bediscussed in relation to FIG. 18. FIG. 18 illustrates a flowchart of amethod 1800 that is associated with using a roadway signature andassociated signature mapping to localize a vehicle. Method 1800 will bediscussed from the perspective of the detection system 170 of FIGS. 1and 14. While method 1800 is discussed in combination with the detectionsystem 170, it should be appreciated that the method 1800 is not limitedto being implemented within the detection system 170, but is instead oneexample of a system that may implement the method 1800.

At 1810, the monitoring module 1410 scans the roadway by transmitting ascanning signal at a surface of the roadway. In one embodiment, themonitoring module 1410 scans the roadway by causing the radar 123 togenerate at least one scanning signal in a similar fashion as discussedin relation to 1010 of FIG. 10. Thus, as discussed previously, inrelation to block 310 of method 300 and block 1010 of FIG. 10, thescanning signal is a radar signal that is generated to have definedcharacteristics. For example, the scanning signal has a definedwavelength, intensity, and frequency. Moreover, while a single scanningsignal is discussed, it should be appreciated that the scanning signalcan be comprised of multiple separate scanning signals from separatesensors within a radar array and/or separate signals over time.

Additionally, while block 1810 is illustrated as a single discreteelement, in one embodiment, the monitoring module 1410 controls theradar sensor 123 to continuously or at least semi-continuously transmitthe scanning signal so that the roadway signature is continually scannedas the vehicle 100 progresses along the roadway. In this way, thedetection system 170 can acquire information from the continuous roadwaysignatures while traveling.

At 1820, the monitoring module 1410 receives a reflected signalresulting from the scanning signal interacting with the roadway. Asnoted previously, while a single discrete signal is discussed, invarious implementations the monitoring module 1410 continuously or atleast semi-continuously receives reflected signals from the radar sensor123 continually scanning the roadway. Furthermore, in one embodiment,the monitoring module 1410 receives the reflected signals in a similaras discussed in relation to the identification module 820 at block 1020of method 1000. Accordingly, the reflected signals are indicative ofproperties of the surface of the roadway. For example, depending onproperties of materials that comprise the roadway, the definedcharacteristics are altered in different ways to produce the reflectedsignals. Thus, the reflected signals embody aspects of the surface ofthe roadway. Consequently, when the roadway signature is applied to theroadway using a material that attenuates the scanning signal, thereflected signal will have a characteristic lower intensity or not bereflected at all. Similarly, materials with a relatively higherreflectivity, or with phase shifting characteristics will inducecorresponding changes in the scanning signal to produce the reflectedsignal.

At 1830, the monitoring module 1410 determines whether one or moreindicators of a roadway signature are present within a reflected signalfrom the roadway. As discussed in relation to the identification module820 and block 1030 previously, the monitoring module 1410 executes in asimilar fashion to detect the continuous roadway signature. That is, themonitoring module 1410 monitors characteristics of the reflected signalsfor indicators that correspond to the roadway signature. As previouslymentioned, the indicators can be defined in, for example, the signatureschema 810 and generally include threshold values relating to signalintensity, phase, and other characteristics of the reflected signalrelative to the scanning signal.

As an additional matter, because the continuous roadway signature is,for example, generally continuous and thus present wherever the vehicle100 is located throughout the roadway, the process of detecting theroadway signature at 1830 is generally focused on determining a segmentof the roadway signature along with detecting a general presence of theroadway signature. Thus, in one embodiment, the monitoring module 1410detects a segment of the roadway signature over a registration windowprior to proceeding to computing an identifier at 1840. The registrationwindow is, in one embodiment, an area within which the detection system170 focuses analysis and that generally aligns with a location on whichthe radar sensor 123 is focused.

Thus, the registration window is generally focused on a segment of theroadway signature with a defined width across the roadway and definedlength along the roadway. As one example, the registration window may bea standardized width that correlates to an average width between frontwheels of a vehicle while having a length along the roadway that is, forexample, several feet. Of course, these dimensions are intended only asan example and particular dimensions of the registration window may beselected according to a particular implementation.

Additionally, in one embodiment, the registration window is dynamic withrespect to a segment of the roadway which is bounded by the registrationwindow as the vehicle 100 travels along. Thus, the registration windowis, for example, continuously moved in either a step-wise manner or asliding manner to correspond with movement of the vehicle 100. Forexample, in the instance of being moved in a step-wise manner, portionsof the roadway signature from a previous window would not occur in asubsequent window. Thus, the step-wise registration windows would be,for example, consecutive segments along the roadway that do not overlap.By contrast, the sliding registration window is continuously progressedalong with movement of the vehicle 100 to include new portions of theroadway signature while sliding past older segments. In one embodiment,the sliding registration window can be modeled in a similar manner as afirst-in first-out (FIFO) buffer.

In either case, at 1830, the monitoring module 1410 monitors for theindicators and, in one embodiment, monitors for the indicators tosubstantially fill a registration window so that the monitoring module1410 can confirm the roadway signature is present prior to proceedingwith computing the identifier at 1840.

At 1840, the monitoring module 1410 computes an identifier for thesegment of the roadway signature within the registration window. In oneembodiment, the monitoring module 1410 computes the identifier at 1840in a similar manner as discussed previously in relation to the signaturemodule 830 and block 1040 of method 1000. Thus, for purposes of brevity,discussion of computing the identifier will not be reiterated. However,it should be appreciated that the monitoring module 1410 computes theidentifier for the segment of the roadway signature that is within theregistration window. Thus, an initial identifier that is computed atblock 1840 is for an initial detection of the roadway signature when,for example, the vehicle 100 is initialized, turns onto a roadway thatincludes the signature, resets scanning of the signature and so on. Ineither case, the identifier that is produced by the monitoring module1410 is a unique characterization of the segment of the roadwaysignature that is bounded by the registration window.

At 1850, the monitoring module 1410 acquires a fix on the roadwaysignature. In one embodiment, the monitoring module 1410 acquires thefix as a function of the one or more indicators that uniquely identifythe segment of the roadway signature. That is, the monitoring module1410 uses the identifier computed at block 1840 and which characterizesthe indicators of the roadway signature to acquire the fix. In oneembodiment, acquiring the fix refers to identifying where within theroadway signature the segment is located and by extension where thevehicle 100 is located so that subsequent segments can be correlated tothe signature mapping 1400.

In one embodiment, the monitoring module 1410 references the signaturemapping 1400 as a manner of determining the segment of the roadwaysignature. For example, the signature mapping 1400, in one embodiment,is a mapping between identifiers of the roadway signature and differentsegments of the roadway. For example, in one embodiment, the monitoringmodule 1410 acquires the fix by computing a moving average over multipleidentifiers (e.g., as checksums) for multiple segments in order tocorrelate a larger section of the roadway with the signature mapping1400. In this way, the monitoring module 1410 can refine a segment ofthe signature mapping 1400 that is being searched and can also adjustthe registration window to align with, for example, a preferredorientation for acquiring the roadway signature. In general, the fixrefers to the monitoring module 1410 determining a correspondencebetween the computed identifier(s) and identifiers defined in thesignature mapping 1400. Thus, the monitoring module 1410 acquires thefix in a similar fashion as a GPS receiver locks onto satellites. Thus,in order to acquire the fix, the monitoring module 1410 determines wherewithin the roadway signature, in correspondence with the signaturemapping 1400, the acquired segment of the roadway signature is located.

However, if, for example, the identifier does not match the signaturemapping 1400, then the identifier can be recomputed at 1840 over asubsequent section, by adjusting the registration window over thepresent segment, or by otherwise re-computing the identifier in order toalign the registration window with segments of the roadway signature ascorrelated in the signature mapping 1400. In this way, subsequentsegments of the roadway signature can be anticipated, and the vehicle100 can be localized as will be discussed further in relation to block1860.

It should be noted, that while the signature mapping 1400 is discussedas being a mapping of identifiers of the roadway signature andrespective locations of the identifiers within the roadway, in variousembodiments, the signature mapping 1400 may instead be a reproduction ofthe roadway signature that is overlaid onto a cartographic mapping ofthe roadway and/or a satellite image based mapping of the roadway.Moreover, the signature mapping 1400, in one embodiment, includesadditional information that corresponds to aspects of the roadway inrelation to respective ones of the identifiers. That is, the identifiersin the signature mapping 1400 can include additional metadata thatindicates a proximity to traffic signals and other roadway features.Additionally, in one embodiment, the identifiers in the signaturemapping 1400 can be linked with alerts and/or other information that isprovided to occupants of the vehicle 100 upon passing the particularsegment of the roadway signature on the roadway.

At 1860, the localization module 1420 localizes the vehicle 100 on theroadway according to the signature mapping 1400. In one embodiment, thelocalization module 1420 identifies a location for the segment of theroadway signature on the roadway and uses the indicated location as alocation of the vehicle 100. In general, the localization module 1420locates the vehicle both along the roadway in a longitudinal y-dimensionand also in a horizontal x-dimension in relation to where within a lanethe vehicle 100 is located. Thus, the localization module 1420 candetermine a precise location for facilitating autonomously controllingthe vehicle and/or otherwise navigating the vehicle along a route.

Accordingly, the roadway signature can uniquely identify a locationalong a width of the roadway by varying as the vehicle 100 moves towardlane markers. That is, the roadway signature is configured so that asthe vehicle 100 moves toward one side of the roadway within a lane, theregistration window moves over a skewed/different segment of the roadwaysignature. Accordingly, the detection system 170 computes an identifierthat is unique to the particular location within the lane in ahorizontal component and in a longitudinal component. Thus, while theregistration window was discussed in various embodiments as the vehicle100 moves along the roadway, the registration window similarly can beshifted from side-to-side within a lane. Consequently, the identifierreflects the precise location within the roadway in relation to theroadway signature.

Moreover, in one embodiment, the localization module 1420 continuouslyor at least semi-continuously tracks the location of the vehicle 100 bycomputing an identifier for each subsequent segment of the roadwaysignature. Accordingly, the localization module 1420 can determine aprecise location by referencing the identifiers against the signaturemapping 1400, but can also determine, for example, a trajectory.Additionally, while localization of the vehicle 100 and the computationof the identifiers are discussed as discrete computations andcomparisons, in one embodiment, the localization module 1420 localizesthe vehicle 100 by computing a moving average of the identifiers and/orby computing the identifiers at a rate (e.g., every 0.1 seconds) that issufficient to precisely track the vehicle 100 along the roadway usingthe signature mapping 1400. In this way, the detection system 170 candetermine a location of the vehicle 100 to autonomously control thevehicle 100 without using, for example, additional sensors such as LIDARsensors to localize the vehicle according to other methods.

As a further matter, information that is used to form the signaturemapping 1400 itself is, in one embodiment, sourced from a plurality ofvehicles traveling on various roadways. For example, the information ofthe signature mapping 1400 can be stored in a cloud-based storage orother distributed storage and can be updated from data that is streamedfrom the plurality of vehicles. Accordingly, modifications to theroadway signature from wear, construction, and/or other circumstancescan be tracked and the signature mapping 1400 can be maintained inreal-time as an accurate representation of the roadway signature.Therefore, in one embodiment, the detection system 170 providesmechanisms to improve how the vehicle 100 detects markers on a roadwayand/or how the vehicle 100 determines a location on the roadway.

FIG. 1 will now be discussed in full detail as an example environmentwithin which the system and methods disclosed herein may operate. Insome instances, the vehicle 100 is configured to switch selectivelybetween an autonomous mode, one or more semi-autonomous operationalmodes, and/or a manual mode. Such switching can be implemented in asuitable manner, now known or later developed. “Manual mode” means thatall of or a majority of the navigation and/or maneuvering of the vehicleis performed according to inputs received from a user (e.g., humandriver). In one or more arrangements, the vehicle 100 can be aconventional vehicle that is configured to operate in only a manualmode.

In one or more embodiments, the vehicle 100 is an autonomous vehicle. Asused herein, “autonomous vehicle” refers to a vehicle that operates inan autonomous mode. “Autonomous mode” refers to navigating and/ormaneuvering the vehicle 100 along a travel route using one or morecomputing systems to control the vehicle 100 with minimal or no inputfrom a human driver. In one or more embodiments, the vehicle 100 ishighly automated or completely automated. In one embodiment, the vehicle100 is configured with one or more semi-autonomous operational modes inwhich one or more computing systems perform a portion of the navigationand/or maneuvering of the vehicle along a travel route, and a vehicleoperator (i.e., driver) provides inputs to the vehicle to perform aportion of the navigation and/or maneuvering of the vehicle 100 along atravel route.

The vehicle 100 can include one or more processors 110. In one or morearrangements, the processor(s) 110 can be a main processor of thevehicle 100. For instance, the processor(s) 110 can be an electroniccontrol unit (ECU). The vehicle 100 can include one or more data stores115 for storing one or more types of data. The data store 115 caninclude volatile and/or non-volatile memory. Examples of suitable datastores 115 include RAM (Random Access Memory), flash memory, ROM (ReadOnly Memory), PROM (Programmable Read-Only Memory), EPROM (ErasableProgrammable Read-Only Memory), EEPROM (Electrically ErasableProgrammable Read-Only Memory), registers, magnetic disks, opticaldisks, hard drives, or any other suitable storage medium, or anycombination thereof. The data store 115 can be a component of theprocessor(s) 110, or the data store 115 can be operatively connected tothe processor(s) 110 for use thereby. The term “operatively connected,”as used throughout this description, can include direct or indirectconnections, including connections without direct physical contact.

In one or more arrangements, the one or more data stores 115 can includemap data 116. The map data 116 can include maps of one or moregeographic areas. In some instances, the map data 116 can includeinformation or data on roads, traffic control devices, road markings,structures, features, and/or landmarks in the one or more geographicareas. The map data 116 can be in any suitable form. In some instances,the map data 116 can include aerial views of an area. In some instances,the map data 116 can include ground views of an area, including360-degree ground views. The map data 116 can include measurements,dimensions, distances, and/or information for one or more items includedin the map data 116 and/or relative to other items included in the mapdata 116. The map data 116 can include a digital map with informationabout road geometry. The map data 116 can be high quality and/or highlydetailed.

In one or more arrangement, the map data 116 can include one or moreterrain maps 117. The terrain map(s) 117 can include information aboutthe ground, terrain, roads, surfaces, and/or other features of one ormore geographic areas. The terrain map(s) 117 can include elevation datain the one or more geographic areas. The map data 116 can be highquality and/or highly detailed. The terrain map(s) 117 can define one ormore ground surfaces, which can include paved roads, unpaved roads,land, and other things that define a ground surface.

In one or more arrangement, the map data 116 can include one or morestatic obstacle maps 118. The static obstacle map(s) 118 can includeinformation about one or more static obstacles located within one ormore geographic areas. A “static obstacle” is a physical object whoseposition does not change or substantially change over a period of timeand/or whose size does not change or substantially change over a periodof time. Examples of static obstacles include trees, buildings, curbs,fences, railings, medians, utility poles, statues, monuments, signs,benches, furniture, mailboxes, large rocks, hills. The static obstaclescan be objects that extend above ground level. The one or more staticobstacles included in the static obstacle map(s) 118 can have locationdata, size data, dimension data, material data, and/or other dataassociated with it. The static obstacle map(s) 118 can includemeasurements, dimensions, distances, and/or information for one or morestatic obstacles. The static obstacle map(s) 118 can be high qualityand/or highly detailed. The static obstacle map(s) 118 can be updated toreflect changes within a mapped area.

The one or more data stores 115 can include sensor data 119. In thiscontext, “sensor data” means any information produced from or about thesensors that the vehicle 100 is equipped with, including thecapabilities and other information about such sensors. As will beexplained below, the vehicle 100 can include the sensor system 120. Thesensor data 119 can relate to one or more sensors of the sensor system120. As an example, in one or more arrangements, the sensor data 119 caninclude information on one or more LIDAR sensors 124 of the sensorsystem 120.

In some instances, at least a portion of the map data 116 and/or thesensor data 119 can be located in one or more data stores 115 locatedonboard the vehicle 100. Alternatively, or in addition, at least aportion of the map data 116 and/or the sensor data 119 can be located inone or more data stores 115 that are located remotely from the vehicle100.

As noted above, the vehicle 100 can include the sensor system 120. Thesensor system 120 can include one or more sensors. “Sensor” means anydevice, component and/or system that can detect, and/or sense something.The one or more sensors can be configured to detect, and/or sense inreal-time. As used herein, the term “real-time” means a level ofprocessing responsiveness that a user or system senses as sufficientlyimmediate for a particular process or determination to be made, or thatenables the processor to keep up with some external process.

In arrangements in which the sensor system 120 includes a plurality ofsensors, the sensors can work independently from each other.Alternatively, two or more of the sensors can work in combination witheach other. In such case, the two or more sensors can form a sensornetwork. The sensor system 120 and/or the one or more sensors can beoperatively connected to the processor(s) 110, the data store(s) 115,and/or another element of the vehicle 100 (including any of the elementsshown in FIG. 1). The sensor system 120 can acquire data of at least aportion of the external environment of the vehicle 100 (e.g., nearbyvehicles).

The sensor system 120 can include any suitable type of sensor. Variousexamples of different types of sensors will be described herein.However, it will be understood that the embodiments are not limited tothe particular sensors described. The sensor system 120 can include oneor more vehicle sensors 121. The vehicle sensor(s) 121 can detect,determine, and/or sense information about the vehicle 100 itself. In oneor more arrangements, the vehicle sensor(s) 121 can be configured todetect, and/or sense position and orientation changes of the vehicle100, such as, for example, based on inertial acceleration. In one ormore arrangements, the vehicle sensor(s) 121 can include one or moreaccelerometers, one or more gyroscopes, an inertial measurement unit(IMU), a dead-reckoning system, a global navigation satellite system(GNSS), a global positioning system (GPS), a navigation system 147,and/or other suitable sensors. The vehicle sensor(s) 121 can beconfigured to detect, and/or sense one or more characteristics of thevehicle 100. In one or more arrangements, the vehicle sensor(s) 121 caninclude a speedometer to determine a current speed of the vehicle 100.

Alternatively, or in addition, the sensor system 120 can include one ormore environment sensors 122 configured to acquire, and/or sense drivingenvironment data. “Driving environment data” includes data orinformation about the external environment in which an autonomousvehicle is located or one or more portions thereof. For example, the oneor more environment sensors 122 can be configured to detect, quantifyand/or sense obstacles in at least a portion of the external environmentof the vehicle 100 and/or information/data about such obstacles. Suchobstacles may be stationary objects and/or dynamic objects. The one ormore environment sensors 122 can be configured to detect, measure,quantify and/or sense other things in the external environment of thevehicle 100, such as, for example, lane markers, signs, traffic lights,traffic signs, lane lines, crosswalks, curbs proximate to the vehicle100, off-road objects, and so on.

Various examples of sensors of the sensor system 120 will be describedherein. The example sensors may be part of the one or more environmentsensors 122 and/or the one or more vehicle sensors 121. However, it willbe understood that the embodiments are not limited to the particularsensors described.

As an example, in one or more arrangements, the sensor system 120 caninclude one or more radar sensors 123, one or more LIDAR sensors 124,one or more sonar sensors 125, and/or one or more cameras 126. In one ormore arrangements, the one or more cameras 126 can be high dynamic range(HDR) cameras or infrared (IR) cameras.

The vehicle 100 can include an input system 130. The input system 130can encompass any device, or system that enables information/data to beentered into a machine. The input system 130 can receive an input from avehicle passenger (e.g. a driver or a passenger). The vehicle 100 caninclude an output system 135. The output system 135 includes any devicethat enables information/data to be presented to a vehicle passenger(e.g. a person, a vehicle passenger, etc.).

The vehicle 100 can include one or more vehicle systems 140. Variousexamples of the one or more vehicle systems 140 are shown in FIG. 1.However, the vehicle 100 can include more, fewer, or different vehiclesystems. It should be appreciated that although particular vehiclesystems are separately defined, each or any of the systems or portionsthereof may be otherwise combined or segregated via hardware and/orsoftware within the vehicle 100. The vehicle 100 can include apropulsion system 141, a braking system 142, a steering system 143,throttle system 144, a transmission system 145, a signaling system 146,and/or a navigation system 147. Each of these systems can include one ormore devices, components, and/or combination thereof, now known or laterdeveloped.

The navigation system 147 can include one or more devices, applications,and/or combinations thereof, now known or later developed, configured todetermine the geographic location of the vehicle 100 and/or to determinea travel route for the vehicle 100. The navigation system 147 caninclude one or more mapping applications to determine a travel route forthe vehicle 100. The navigation system 147 can include a globalpositioning system, a local positioning system or a geolocation system.

The processor(s) 110, the detection system 170, and/or the autonomousdriving module(s) 160 can be operatively connected to communicate withthe various vehicle systems 140 and/or individual components thereof.For example, returning to FIG. 1, the processor(s) 110 and/or theautonomous driving module(s) 160 can be in communication to send and/orreceive information from the various vehicle systems 140 to control themovement, speed, maneuvering, heading, direction, etc. of the vehicle100. The processor(s) 110, the detection system 170, and/or theautonomous driving module(s) 160 may control some or all of thesevehicle systems 140 and, thus, may be partially or fully autonomous.

The processor(s) 110, the detection system 170, and/or the autonomousdriving module(s) 160 can be operatively connected to communicate withthe various vehicle systems 140 and/or individual components thereof.For example, returning to FIG. 1, the processor(s) 110, the detectionsystem 170, and/or the autonomous driving module(s) 160 can be incommunication to send and/or receive information from the variousvehicle systems 140 to control the movement, speed, maneuvering,heading, direction, etc. of the vehicle 100. The processor(s) 110, thedetection system 170, and/or the autonomous driving module(s) 160 maycontrol some or all of these vehicle systems 140.

The processor(s) 110, the detection system 170, and/or the autonomousdriving module(s) 160 may be operable to control the navigation and/ormaneuvering of the vehicle 100 by controlling one or more of the vehiclesystems 140 and/or components thereof. For instance, when operating inan autonomous mode, the processor(s) 110, the detection system 170,and/or the autonomous driving module(s) 160 can control the directionand/or speed of the vehicle 100. The processor(s) 110, the detectionsystem 170, and/or the autonomous driving module(s) 160 can cause thevehicle 100 to accelerate (e.g., by increasing the supply of fuelprovided to the engine), decelerate (e.g., by decreasing the supply offuel to the engine and/or by applying brakes) and/or change direction(e.g., by turning the front two wheels). As used herein, “cause” or“causing” means to make, force, compel, direct, command, instruct,and/or enable an event or action to occur or at least be in a statewhere such event or action may occur, either in a direct or indirectmanner.

The vehicle 100 can include one or more actuators 150. The actuators 150can be any element or combination of elements operable to modify, adjustand/or alter one or more of the vehicle systems 140 or componentsthereof to responsive to receiving signals or other inputs from theprocessor(s) 110 and/or the autonomous driving module(s) 160. Anysuitable actuator can be used. For instance, the one or more actuators150 can include motors, pneumatic actuators, hydraulic pistons, relays,solenoids, and/or piezoelectric actuators, just to name a fewpossibilities.

The vehicle 100 can include one or more modules, at least some of whichare described herein. The modules can be implemented ascomputer-readable program code that, when executed by a processor 110,implement one or more of the various processes described herein. One ormore of the modules can be a component of the processor(s) 110, or oneor more of the modules can be executed on and/or distributed among otherprocessing systems to which the processor(s) 110 is operativelyconnected. The modules can include instructions (e.g., program logic)executable by one or more processor(s) 110. Alternatively, or inaddition, one or more data store 115 may contain such instructions.

In one or more arrangements, one or more of the modules described hereincan include artificial or computational intelligence elements, e.g.,neural network, fuzzy logic or other machine learning algorithms.Further, in one or more arrangements, one or more of the modules can bedistributed among a plurality of the modules described herein. In one ormore arrangements, two or more of the modules described herein can becombined into a single module.

The vehicle 100 can include one or more autonomous driving modules 160.The autonomous driving module(s) 160 can be configured to receive datafrom the sensor system 120 and/or any other type of system capable ofcapturing information relating to the vehicle 100 and/or the externalenvironment of the vehicle 100. In one or more arrangements, theautonomous driving module(s) 160 can use such data to generate one ormore driving scene models. The autonomous driving module(s) 160 candetermine position and velocity of the vehicle 100. The autonomousdriving module(s) 160 can determine the location of obstacles,obstacles, or other environmental features including traffic signs,trees, shrubs, neighboring vehicles, pedestrians, etc.

The autonomous driving module(s) 160 can be configured to receive,and/or determine location information for obstacles within the externalenvironment of the vehicle 100 for use by the processor(s) 110, and/orone or more of the modules described herein to estimate position andorientation of the vehicle 100, vehicle position in global coordinatesbased on signals from a plurality of satellites, or any other dataand/or signals that could be used to determine the current state of thevehicle 100 or determine the position of the vehicle 100 with respect toits environment for use in either creating a map or determining theposition of the vehicle 100 in respect to map data.

The autonomous driving module(s) 160 either independently or incombination with the detection system 170 can be configured to determinetravel path(s), current autonomous driving maneuvers for the vehicle100, future autonomous driving maneuvers and/or modifications to currentautonomous driving maneuvers based on data acquired by the sensor system120, driving scene models, and/or data from any other suitable source.“Driving maneuver” means one or more actions that affect the movement ofa vehicle. Examples of driving maneuvers include: accelerating,decelerating, braking, turning, moving in a lateral direction of thevehicle 100, changing travel lanes, merging into a travel lane, and/orreversing, just to name a few possibilities. The autonomous drivingmodule(s) 160 can be configured can be configured to implementdetermined driving maneuvers. The autonomous driving module(s) 160 cancause, directly or indirectly, such autonomous driving maneuvers to beimplemented. As used herein, “cause” or “causing” means to make,command, instruct, and/or enable an event or action to occur or at leastbe in a state where such event or action may occur, either in a director indirect manner. The autonomous driving module(s) 160 can beconfigured to execute various vehicle functions and/or to transmit datato, receive data from, interact with, and/or control the vehicle 100 orone or more systems thereof (e.g. one or more of vehicle systems 140).

Detailed embodiments are disclosed herein. However, it is to beunderstood that the disclosed embodiments are intended only as examples.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative basis for teaching one skilled in the artto variously employ the aspects herein in virtually any appropriatelydetailed structure. Further, the terms and phrases used herein are notintended to be limiting but rather to provide an understandabledescription of possible implementations. Various embodiments are shownin FIGS. 1-2, but the embodiments are not limited to the illustratedstructure or application.

The flowcharts and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments. In this regard, each block in the flowcharts or blockdiagrams may represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block may occurout of the order noted in the figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved.

The systems, components and/or processes described above can be realizedin hardware or a combination of hardware and software and can berealized in a centralized fashion in one processing system or in adistributed fashion where different elements are spread across severalinterconnected processing systems. Any kind of processing system oranother apparatus adapted for carrying out the methods described hereinis suited. A typical combination of hardware and software can be aprocessing system with computer-usable program code that, when beingloaded and executed, controls the processing system such that it carriesout the methods described herein. The systems, components and/orprocesses also can be embedded in a computer-readable storage, such as acomputer program product or other data programs storage device, readableby a machine, tangibly embodying a program of instructions executable bythe machine to perform methods and processes described herein. Theseelements also can be embedded in an application product which comprisesall the features enabling the implementation of the methods describedherein and, which when loaded in a processing system, is able to carryout these methods.

Furthermore, arrangements described herein may take the form of acomputer program product embodied in one or more computer-readable mediahaving computer-readable program code embodied, e.g., stored, thereon.Any combination of one or more computer-readable media may be utilized.The computer-readable medium may be a computer-readable signal medium ora computer-readable storage medium. The phrase “computer-readablestorage medium” means a non-transitory storage medium. Acomputer-readable storage medium may be, for example, but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer-readable storage medium would include the following: a portablecomputer diskette, a hard disk drive (HDD), a solid-state drive (SSD), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a portable compact disc read-only memory (CD-ROM), adigital versatile disc (DVD), an optical storage device, a magneticstorage device, or any suitable combination of the foregoing. In thecontext of this document, a computer-readable storage medium may be anytangible medium that can contain, or store a program for use by or inconnection with an instruction execution system, apparatus, or device.

Program code embodied on a computer-readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber, cable, RF, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present arrangements may be written in any combination ofone or more programming languages, including an object-orientedprogramming language such as Java™ Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer, or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

The terms “a” and “an,” as used herein, are defined as one or more thanone. The term “plurality,” as used herein, is defined as two or morethan two. The term “another,” as used herein, is defined as at least asecond or more. The terms “including” and/or “having,” as used herein,are defined as comprising (i.e. open language). The phrase “at least oneof . . . and . . . ” as used herein refers to and encompasses any andall possible combinations of one or more of the associated listed items.As an example, the phrase “at least one of A, B, and C” includes A only,B only, C only, or any combination thereof (e.g. AB, AC, BC or ABC).

Aspects herein can be embodied in other forms without departing from thespirit or essential attributes thereof. Accordingly, reference should bemade to the following claims, rather than to the foregoingspecification, as indicating the scope hereof.

What is claimed is:
 1. A detection system for detecting a marker on aroadway, comprising: one or more processors; a memory communicablycoupled to the one or more processors and storing: a scanning moduleincluding instructions that when executed by the one or more processorscause the one or more processors to control a radar to actively transmita scanning signal with defined characteristics including a wavelengthwithin a radar-band of the electromagnetic spectrum that is anon-visible portion of the electromagnetic spectrum, wherein the radaris integrated with a vehicle that is traveling on the roadway; and adetection module including instructions that when executed by the one ormore processors cause the one or more processors to, in response toreceiving a reflected signal resulting from the scanning signalinteracting with the roadway, identify the marker from the reflectedsignal according to an electromagnetic signature of the marker embodiedin the reflected signal including identifying the electromagneticsignature according to a contrasting region in the roadway having acontrasting reflectivity of the wavelength in comparison to surroundingsections of the roadway, wherein the electromagnetic signature is aresponse induced within the defined characteristics of the scanningsignal that is embodied within the reflected signal, and wherein thecontrasting region is an area with a relatively lower reflectivity forthe wavelength within the electromagnetic spectrum than the surroundingsections and that is induced within the reflected signal when thescanning signal is reflected from the marker comprised ofelectromagnetic radiation absorbing material.
 2. The detection system ofclaim 1, wherein the marker is one of a lane marker and a surfacetraffic marker, wherein the scanning signal and the reflected signal areelectromagnetic radiation within a radar band of the electromagneticspectrum, wherein the detection module further includes instructions toidentify the marker according to the electromagnetic signature byidentifying the electromagnetic signature as one or more of: (i) acontrasting region in the roadway that is characterized by asubstantially contrasting reflectivity in comparison to surroundingsections of the roadway, and (ii) a phase region in the roadway that ischaracterized by a defined phase shift as a response produced in thereflected signal relative to the defined characteristics of the scanningsignal.
 3. The detection system of claim 2, wherein the detection modulefurther includes instructions to identify the marker by: (i) analyzingthe reflected signal to locate the contrasting region within theroadway, and (ii) determining whether a shape of the contrasting regioncorrelates with a type of the marker and an expected location within theroadway.
 4. The detection system of claim 1, wherein the detectionmodule further includes instructions to identify whether a roadway codeis present within the marker according to an outlined shape of theelectromagnetic signature within the marker and between successivemarkers along the roadway.
 5. The detection system of claim 4, whereinthe detection module further includes instructions to decode the markeraccording to a marker schema to provide embedded information of theroadway code as output to the vehicle in response to determining thatthe marker includes the roadway code.
 6. The detection system of claim5, wherein the embedded information is one of: a barcode, a binary code,a ternary code, and a QR code, and wherein the detection module furtherincludes instructions to identify the marker by determining whether thedetermined shape, area, and electromagnetic signature satisfy a markerthreshold that indicates a confidence interval for accepting adetermined shape, area, and electromagnetic signature as indicating apresence of the marker.
 7. The detection system of claim 4, wherein thescanning module further includes instructions to control the vehicleaccording to the identified marker and associated embedded information,and wherein the embedded information includes information about theroadway.
 8. The detection system of claim 1, wherein the scanning modulefurther includes instructions to receive the reflected signal when asurface of the roadway is covered with precipitation, and wherein theradar is an array of radar sensors located within a forward section ofthe vehicle and oriented toward the surface of the roadway.
 9. Anon-transitory computer-readable medium storing instructions that whenexecuted by one or more processors cause the one or more processors to:control a radar to actively transmit a scanning signal with definedcharacteristics including a wavelength within a radar-band of theelectromagnetic spectrum that is a non-visible portion of theelectromagnetic spectrum, wherein the radar is integrated with a vehiclethat is traveling on a roadway; and in response to receiving a reflectedsignal resulting from the scanning signal interacting with the roadway,identify a marker within the roadway from the reflected signal accordingto an electromagnetic signature of the marker embodied in the reflectedsignal including identifying the electromagnetic signature according toa contrasting region in the roadway having a contrasting reflectivity ofthe wavelength in comparison to surrounding sections of the roadway,wherein the electromagnetic signature is a response induced within thedefined characteristics of the scanning signal that is embodied withinthe reflected signal, and wherein the contrasting region is an area witha relatively lower reflectivity for the wavelength within theelectromagnetic spectrum than the surrounding sections and that isinduced within the reflected signal when the scanning signal isreflected from the marker comprised of electromagnetic radiationabsorbing material.
 10. The non-transitory computer-readable medium ofclaim 9, wherein the marker is one of a lane marker and a surfacetraffic marker.
 11. The non-transitory computer-readable medium of claim9, wherein the instructions identify the marker according to theelectromagnetic signature further include instructions to identify theelectromagnetic signature as one or more of: (i) a contrasting region inthe roadway that is characterized by a substantially contrastingreflectivity in comparison to surrounding segments of the roadway, and(ii) a phase region in the roadway that is characterized by a definedphase shift relative to the defined characteristics of the scanningsignal.
 12. The non-transitory computer-readable medium of claim 9,wherein the instructions further include instructions to identifywhether a roadway code is present within the marker according to anoutlined shape of the electromagnetic signature within the marker andbetween successive markers along the roadway, and wherein theinstructions further include instructions to decode the marker accordingto a marker schema to provide embedded information of the roadway codeas output to the vehicle in response to determining that the markerincludes the roadway code.
 13. The non-transitory computer-readablemedium of claim 9, wherein the instructions include instructions toreceive the reflected signal when a surface of the roadway is coveredwith precipitation, and wherein the radar is an array of radar sensorslocated within a forward section of the vehicle and oriented toward thesurface of the roadway.
 14. A method of detecting a marker on a roadway,comprising: controlling a radar to actively transmit a scanning signalwith defined characteristics including a wavelength within a radar-bandof the electromagnetic spectrum that is a non-visible portion of theelectromagnetic spectrum, wherein the radar is integrated with a vehiclethat is traveling on the roadway; and in response to receiving areflected signal resulting from the scanning signal interacting with theroadway, identifying the marker from the reflected signal according toan electromagnetic signature of the marker embodied in the reflectedsignal including identifying the electromagnetic signature according toa contrasting region in the roadway having a contrasting reflectivity ofthe wavelength in comparison to surrounding sections of the roadway,wherein the electromagnetic signature is a response induced within thedefined characteristics of the scanning signal that is embodied withinthe reflected signal, and wherein the contrasting region is an area witha relatively lower reflectivity for the wavelength within theelectromagnetic spectrum than the surrounding sections and that isinduced within the reflected signal when the scanning signal isreflected from the marker comprised of electromagnetic radiationabsorbing material.
 15. The method of claim 14, wherein the marker isone of a lane marker, and a surface traffic marker, wherein the scanningsignal and the reflected signal are electromagnetic radiation, whereinidentifying the marker according to the electromagnetic signatureincludes identifying the electromagnetic signature as one or more of:(i) a contrasting region in the roadway that is characterized by ahighly contrasting reflectivity in comparison to surrounding sections ofthe roadway, and (ii) a phase region in the roadway that ischaracterized by a defined phase shift as a response produced in thereflected signal relative to the defined characteristics of the scanningsignal.
 16. The method of claim 15, wherein identifying the markerincludes (i) analyzing the reflected signal to locate the contrastingregion within the roadway, and (ii) determining whether a shape of thecontrasting region correlates with a type of the marker and an expectedlocation within the roadway.
 17. The method of claim 14, furthercomprising: identifying whether a roadway code is present within themarker according to an outlined shape of the electromagnetic signaturewithin the marker and between successive markers along the roadway. 18.The method of claim 17, wherein identifying whether the roadway code ispresent includes decoding the marker according to a marker schema toprovide embedded information of the roadway code as output to thevehicle in response to determining that the marker includes the roadwaycode.
 19. The method of claim 17, wherein the roadway code is one of: abarcode, a binary code, a ternary code, and a QR code, and whereinidentifying the marker includes determining whether a determined shape,area, and electromagnetic signature to satisfy a marker threshold,wherein identifying the marker includes determining whether thedetermined shape, area, and electromagnetic signature satisfy a markerthreshold that indicates a confidence interval for accepting thedetermined shape, area, and electromagnetic signature as indicating apresence of the marker.
 20. The method of claim 17, further comprising:controlling the vehicle according to the identified marker andassociated embedded information, wherein the embedded informationincludes information about the roadway, and wherein controlling thevehicle includes autonomously controlling the vehicle.